Nuclear pleomorphism in canine cutaneous mast cell tumors: Comparison of reproducibility and prognostic relevance between estimates, manual morphometry, and algorithmic morphometry.

Variation in nuclear size and shape is an important criterion of malignancy for many tumor types; however, categorical estimates by pathologists have poor reproducibility. Measurements of nuclear characteristics can improve reproducibility, but current manual methods are time-consuming. The aim of this study was to explore the limitations of estimates and develop alternative morphometric solutions for canine cutaneous mast cell tumors (ccMCTs).

Association of daily physical activity with pulmonary artery pressure in HFpEF and HFmrEF NYHA class III patients: a pilot trial-feasibility and first results.

Introduction: Supervised physical exercise has been shown to benefit patients with heart failure with preserved/mildly reduced ejection fraction (HFpEF/HfmrEF) by improving symptoms and diastolic function. This study aimed to investigate the correlation between unsupervised daily physical activity and changes in daily pulmonary artery pressure (PAP) in patients with stable NYHA class III heart failure (HF) and left ventricular ejection fraction (LVEF) of 45% or higher.

Methods: Daily physical activity was monitored over a 3-month period using a Holter-ECG with an accelerometer that calculated an activity-associated, heart rate-derived metabolic equivalent of task (MET) score.

Information mismatch in PHH3-assisted mitosis annotation leads to interpretation shifts in H&E slide analysis.

The count of mitotic figures (MFs) observed in hematoxylin and eosin (H&E)-stained slides is an important prognostic marker, as it is a measure for tumor cell proliferation. However, the identification of MFs has a known low inter-rater agreement. In a computer-aided setting, deep learning algorithms can help to mitigate this, but they require large amounts of annotated data for training and validation.

Re-identification from histopathology images.

In numerous studies, deep learning algorithms have proven their potential for the analysis of histopathology images, for example, for revealing the subtypes of tumors or the primary origin of metastases. These models require large datasets for training, which must be anonymized to prevent possible patient identity leaks. This study demonstrates that even relatively simple deep learning algorithms can re-identify patients in large histopathology datasets with substantial accuracy.

Prediction of tumor board procedural recommendations using large language models.

Introduction: Multidisciplinary tumor boards are meetings where a team of medical specialists, including medical oncologists, radiation oncologists, radiologists, surgeons, and pathologists, collaborate to determine the best treatment plan for cancer patients. While decision-making in this context is logistically and cost-intensive, it has a significant positive effect on overall cancer survival. METHODS : We evaluated the quality and accuracy of predictions by several large language models for recommending procedures by a Head and Neck Oncology tumor board, which we adapted for the task using parameter-efficient fine-tuning or in-context learning.

[Not Available].

The aim of the interdisciplinary S2k guideline "Acute infectious gastroenteritis in infants, children and adolescents" is to summarise the current state of knowledge on the clinical presentation, diagnosis, treatment, prevention and hygiene of acute infectious gastroenteritis, including nosocomial gastrointestinal infections, in infants, children and adolescents on the basis of scientific evidence, to evaluate it by expert consensus and to derive practice-relevant recommendations from it. The guideline provides a corridor for action for frequent decisions. It also serves the purpose of evidence-based further education and training and is thus intended to improve the medical care of children with acute gastroenteritis.

Colloidal spherical stibnite particles high-temperature metallo-organic synthesis.

Antimony trisulfide (SbS) is an emerging semiconductor with a high absorption coefficient and a bandgap in the visible range. This makes it a promising material for various electronic and optoelectronic applications. However, one of the main challenges is still the synthesis of the material, as it is usually obtained either as a nanomaterial in its amorphous form with inferior optical properties or in crystalline rod-like structures in the micrometer or sub-micrometer range, which leads to application-related difficulties such as clogging in inkjet printing or spraying processes or highly porous layers in film applications.

From perception to action: Waste management challenges in Kassena Nankana East Municipality.

This study examines the perceptions and behaviours related to waste management (WM) among residents of the Kassena Nankana East Municipality in Ghana. A mixed-method approach was used to garner data from 394 household respondents, and the data was analysed using SPSS software. The findings reveal a weak correlation between educational attainment and effective waste management practices and a mildly positive correlation between waste awareness and the effectiveness of policies and legislation.

Comparative analysis of FDA approvals by top 20 pharma companies (2014-2023).

This article addresses the research and development (R&D) productivity challenge of the pharmaceutical industry, focusing on United States Food and Drug Administration (FDA)-related new drug approvals of the top 20 pharmaceutical companies (2014-2023). We evaluated the degree of innovation in new drugs to determine the innovativeness of these leading companies. A key finding of our analysis is the decline in the number of new drugs approved by the FDA for these leading companies over the investigated time period.

Adapted Design Process for Continuous Fiber-Reinforced Additive Manufacturing-A Methodological Framework.

Continuous fiber-reinforced material extrusion is an emerging additive manufacturing process that builds components layer by layer by extruding a continuous fiber-reinforced thermoplastic strand. This novel manufacturing process combines the benefits of additive manufacturing with the mechanical properties and lightweight potential of composite materials, making it a promising approach for creating high-strength end products. The field of design for additive manufacturing has developed to provide suitable methods and tools for such emerging processes.

Automated Nuclear Morphometry: A Deep Learning Approach for Prognostication in Canine Pulmonary Carcinoma to Enhance Reproducibility.

The integration of deep learning-based tools into diagnostic workflows is increasingly prevalent due to their efficiency and reproducibility in various settings. We investigated the utility of automated nuclear morphometry for assessing nuclear pleomorphism (NP), a criterion of malignancy in the current grading system in canine pulmonary carcinoma (cPC), and its prognostic implications. We developed a deep learning-based algorithm for evaluating NP (variation in size, i.

SALOS-A UWB Single-Anchor Indoor Localization System Based on a Statistical Multipath Propagation Model.

Among other methods, UWB-based multi-anchor localization systems have been established for industrial indoor localization systems. However, multi-anchor systems have high costs and installation effort. By exploiting the multipath propagation of the UWB signal, the infrastructure and thus the costs of conventional systems can be reduced.

Effects of transcranial direct current stimulation and sensorimotor training in anterior cruciate ligament patients: a sham-controlled pilot study.

Background: Studies showed changes in the central nervous system in patients who sustained an anterior cruciate ligament tear. There is a lack of evidence regarding the effectiveness of transcranial direct-current stimulation in such patients.

Methods: A sham-controlled randomised study.

Definitions of digital biomarkers: a systematic mapping of the biomedical literature.

Background: Technological devices such as smartphones, wearables and virtual assistants enable health data collection, serving as digital alternatives to conventional biomarkers. We aimed to provide a systematic overview of emerging literature on 'digital biomarkers,' covering definitions, features and citations in biomedical research.

Methods: We analysed all articles in PubMed that used 'digital biomarker(s)' in title or abstract, considering any study involving humans and any review, editorial, perspective or opinion-based articles up to 8 March 2023.

Domain generalization across tumor types, laboratories, and species - Insights from the 2022 edition of the Mitosis Domain Generalization Challenge.

Recognition of mitotic figures in histologic tumor specimens is highly relevant to patient outcome assessment. This task is challenging for algorithms and human experts alike, with deterioration of algorithmic performance under shifts in image representations. Considerable covariate shifts occur when assessment is performed on different tumor types, images are acquired using different digitization devices, or specimens are produced in different laboratories.

Post-hoc standardisation of parametric T1 maps in cardiovascular magnetic resonance imaging: a proof-of-concept.

Background: In cardiovascular magnetic resonance imaging parametric T1 mapping lacks universally valid reference values. This limits its extensive use in the clinical routine. The aim of this work was the introduction of our self-developed Magnetic Resonance Imaging Software for Standardization (MARISSA) as a post-hoc standardisation approach.

Auditory Spatial Bisection of Blind and Normally Sighted Individuals in Free Field and Virtual Acoustics.

Sound localization is an important ability in everyday life. This study investigates the influence of vision and presentation mode on auditory spatial bisection performance. Subjects were asked to identify the smaller perceived distance between three consecutive stimuli that were either presented via loudspeakers (free field) or via headphones after convolution with generic head-related impulse responses (binaural reproduction).

Evaluation of Eligibility Criteria Relevance for the Purpose of IT-Supported Trial Recruitment: Descriptive Quantitative Analysis.

Background: Clinical trials (CTs) are crucial for medical research; however, they frequently fall short of the requisite number of participants who meet all eligibility criteria (EC). A clinical trial recruitment support system (CTRSS) is developed to help identify potential participants by performing a search on a specific data pool. The accuracy of the search results is directly related to the quality of the data used for comparison.

High Genetic Diversity in Third-Generation Cephalosporin-Resistant in Wastewater Systems of Schleswig-Holstein.

The spread of multidrug-resistant bacteria from humans or livestock is a critical issue. However, the epidemiology of resistant pathogens across wastewater pathways is poorly understood. Therefore, we performed a detailed comparison of third-generation cephalosporin-resistant (3GCREC) from wastewater treatment plants (WWTPs) to analyze dissemination pathways.

The effect of early skin-to-skin contact after cesarean section on breastfeeding duration and development of atopic-allergic diseases.

Introduction: Breastfeeding to strengthen the immune system suggests allergy prevention as a possible option. The connection between breastfeeding and the development of atopic-allergic diseases is being discussed. The primary aim of this work was to investigate an association of the first early skin-to-skin contact following cesarean section with the development of atopic diseases within the 1st year of life.

Impact of Partially Automated Driving Functions on Forensic Accident Reconstruction: A Simulator Study on Driver Reaction Behavior in the Event of a Malfunctioning System Behavior.

Partially automated driving functions (SAE Level 2) can control a vehicle's longitudinal and lateral movements. However, taking over the driving task involves automation risks that the driver must manage. In severe accidents, the driver's ability to avoid a collision must be assessed, considering their expected reaction behavior.

[Pacemaker, organ or walking stick? Pre-op association with and post-op subjective perception of a deep brain stimulation device].

Aim Of The Study: This study was conducted in a pre-post design with a survey of patients who had undergone deep brain stimulation (DBS) as treatment for a neurological movement disorder. The aim of the study was to compare patients' expectations and beliefs before a DBS intervention with patients' subjective experience of this intervention.

Methodology: The longitudinal study of patients (n=132) with an indication for DBS therapy was based on a written survey at the time points of preoperative screening (pre-op) and one-year follow-up (post-op).

Designing for passengers' information needs on fellow travelers: A comparison of day and night rides in shared automated vehicles.

Shared automated mobility-on-demand promises efficient, sustainable, and flexible transportation. Nevertheless, security concerns, resilience, and their mutual influence - especially at night - will likely be the most critical barriers to public adoption since passengers have to share rides with strangers without a human driver on board. Prior research points out that having information about fellow travelers could alleviate the concerns of passengers and we designed two user interface variants to investigate the role of this information in an exploratory within-subjects user study (N=24).